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OCTOBER 19-20, 2012 - YMCA University of Science & Technology

OCTOBER 19-20, 2012 - YMCA University of Science & Technology

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Proceedings <strong>of</strong> the National Conference on<br />

Trends and Advances in Mechanical Engineering,<br />

<strong>YMCA</strong> <strong>University</strong> <strong>of</strong> <strong>Science</strong> & <strong>Technology</strong>, Faridabad, Haryana, Oct <strong>19</strong>-<strong>20</strong>, <strong>20</strong>12<br />

work very efficiently within their domain. However, the limitation on the size <strong>of</strong> the virtual model and its<br />

complexity limits the scope <strong>of</strong> these systems. A time lag sets in when complex, highly deformable and large sized<br />

virtual models are encountered and real-time interaction may not be possible.There are more research groups [24-<br />

26] using virtual reality for concept design. The virtual concept design tools are in high demand in industry.<br />

1.2. VR Based Design Process<br />

The virtual reality based design process is based on the interaction <strong>of</strong> the user with the virtual model through a<br />

haptic device. There are three distinct processes that need to be performed to carry out the interaction. To<br />

visualize the virtual model and the tool, a ‘haptic rendering system’ is used. The ‘collision detection system’<br />

calculates the relative position <strong>of</strong> the model and the tool at any instance in time. As soon as the haptic tool starts<br />

interacting with the tool, this information about the position <strong>of</strong> contact and the extent <strong>of</strong> penetration is provided<br />

by the collision detection system. Based the information provided by the collision detection algorithm, the<br />

‘physics-based system’ determines the deformation <strong>of</strong> the model(s) and the resultant reactive forces to be fed<br />

back to the user. Figure 2 shows the schematic representation <strong>of</strong> a general virtual reality-based design process.<br />

Figure 2. Schematic Representation Of A Vr-Based Design Process.<br />

1.3. Collision Detection<br />

Collision detection is used in virtual assembly, simulation-based concept design, evaluation <strong>of</strong> design, motion<br />

planning, medical training, virtual reality based games and animation. Collision detection is computationally<br />

intensive and is considered a bottleneck in these applications. A collision detection system automatically reports a<br />

geometric contact between the haptic tool and a virtual object. It calculates when a contact is about to occur or<br />

has actually occurred. There are many collision detection algorithms available in literature. Jimenez [27] surveyed<br />

various collision detection algorithms. It focused on how the model representation leads to different collision<br />

detection algorithms. On the other hand, Lin and Gottschalk [28] presented a survey on the state <strong>of</strong> the art in<br />

collision detection between models represented by smooth surfaces. Pungotra et al [29] proposed an algorithm<br />

that uses B-spline based models and rigid as well as deformable tool. This algorithm uses best <strong>of</strong> parametric<br />

representation <strong>of</strong> surface and efficiency <strong>of</strong> triangle-triangle intersection test.<br />

1.4.Physics Based Deformation Modelling<br />

The deformation <strong>of</strong> the model can be simulated by a geometric- or physics-based system. Geometric techniques,<br />

though efficient, do not yield accurate results which may be required for the evaluation <strong>of</strong> the model. Physicsbased<br />

techniques, on the other hand, yield accurate results. However, the computational cost is large for such<br />

techniques. A mass spring damper system, consisting <strong>of</strong> a set <strong>of</strong> particles (nodes) connected through a network <strong>of</strong><br />

springs and dampers can provide reasonable accuracy and speed for real time interaction. Pungotra et al [30]<br />

proposed the representation <strong>of</strong> B-spline surfaces in terms <strong>of</strong> blending matrices. This facilitated integration <strong>of</strong><br />

collision detection with the mass spring system. The virtual object is modeled as a collection <strong>of</strong> point masses<br />

connected by springs and dampers in a lattice structure. In general, the spring forces are assumed to be linear.<br />

However, nonlinear springs can also be used to model objects which exhibit inelastic behaviour. Such a system<br />

contains a mass ρ, a spring with spring constant K that serves to restore the mass to a neutral position, and a<br />

damping element which opposes the motion <strong>of</strong> the vibratory response with a force proportional to the velocity <strong>of</strong><br />

the system. The constant <strong>of</strong> proportionality, also known as damping constant, is denoted by D. Different<br />

combinations <strong>of</strong> linear springs and damper can be used to model deformable objects. Voigt model is the most<br />

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